CNC Machine Tool's wear diagnostic and prognostic by using dynamic bayesian networks.

International audienceThe failure of critical components in industrial systems may have negative consequences on the availability, the productivity, the security and the environment. To avoid such situations, the health condition of the physical system, and particularly of its critical components, can be constantly assessed by using the monitoring data to perform on-line system diagnostics and prognostics. The present paper is a contribution on the assessment of the health condition of a Computer Numerical Control (CNC) tool machine and the estimation of its Remaining Useful Life (RUL). The proposed method relies on two main phases: an off-line phase and an on-line phase. During the first phase, the raw data provided by the sensors are processed to extract reliable features. These latter are used as inputs of learning algorithms in order to generate the models that represent the wear's behavior of the cutting tool. Then, in the second phase, which is an assessment one, the constructed models are exploited to identify the tool's current health state, predict its RUL and the associated confidence bounds. The proposed method is applied on a benchmark of condition monitoring data gathered during several cuts of a CNC tool. Simulation results are obtained and discussed at the end of the paper

CNC machine tool health assessment using Dynamic Bayesian Networks.

International audienceThe failure of critical components in physical systems may have negative consequences on the availability, the productivity, their security and on the environment. Thus, the assessment of the critical component's health condition, which can be done in the diagnostic and prognostic framework, should be constantly ensured. In this paper, a contribution on the assessment of the health condition of the cutting tool from a Computer Numerical Control (CNC) machine tool and the prediction of its remaining useful life before its complete failure is addressed. The proposed method is based on the use of monitoring data and relies on two main phases: an off-line phase and an on-line phase. During the first phase, the raw data provided by the sensors are processed to extract reliable features. These latter are then fed as inputs to the learning algorithms in order to generate relevant models that best represent the behavior of the cutting tool. The second phase is an assessment one, which uses the constructed models to identify the current health state and to compute the remaining useful life and the associated confidence value. The method is applied on monitoring data gathered during several cuts of the CNC tool and simulation results are given and discussed

A mixture of gaussians hidden markov model for failure diagnostic and prognostic.

International audienceThis paper deals with a data-driven diagnostic and prognostic method based on a Mixture of Gaussians Hidden Markov Model. The prognostic process of the proposed method is made in two steps. In the first step, which is performed offline, the monitoring data provided by sensors are processed to extract features, which are then used to learn different models that capture the time evolution of the degradation and therefore of the system's health state. In the second step, performed online, the learned models are exploited to do failure diagnostic and prognostic by estimating the asset's current health state, its remaining useful life and the associated confidence degree. The proposed method is tested on a benchmark data related to several bearings and simulation results are given at the end of the paper

Hidden Markov models for failure diagnostic and prognostic.

International audienceThis paper deals with an estimation of the Remaining Useful Life of bearings based on the utilization of Mixture of Gaussians Hidden Markov Models (MoG-HMMs). The raw signals provided by the sensors are first processed to extract features, which permit to model the physical component and its degradation. The prognostic process is done in two phases: a learning phase and an evaluation phase. During the first phase, the sensors' data are processed in order to extract appropriate and useful features, which are then used as inputs of dedicated learning algorithms in order to estimate the parameters of a MoG-HMM. The obtained model represents the behavior of the component including its degradation. In addition, the model contains the number of health states and the stay durations in each state. Once the learning phase is done, the generated model is exploited during the second phase, where the extracted features are continuously injected to the learned model to assess the current health state of the physical component and to estimate its remaining useful life and the associated confidence. The proposed method is tested on a benchmark data taken from the "NASA prognostic data repository" related to bearings used under several operating conditions. Moreover, the developed method is compared to two methods: the first using traditional HMMs with exponential time durations and the second using regular Hidden Semi Markov Model (HSMM). Finally, simulation results are given and discussed at the end of the paper

A data-driven failure prognostics method based on mixture of gaussians hidden markov models

International audienceThis paper addresses a data-driven prognostics method for the estimation of the Remaining Useful Life (RUL) and the associated confidence value of bearings. The proposed method is based on the utilization of the Wavelet Packet Decomposition (WPD) technique, and the Mixture of Gaussians Hidden Markov Models (MoG-HMM). The method relies on two phases: an off-line phase, and an on-line phase. During the first phase, the raw data provided by the sensors are first processed to extract features in the form of WPD coefficients. The extracted features are then fed to dedicated learning algorithms to estimate the parameters of a corresponding MoG-HMM, which best fits the degradation phenomenon. The generated model is exploited during the second phase to continuously assess the current health state of the physical component, and to estimate its RUL value with the associated confidence. The developed method is tested on benchmark data taken from the "NASA prognostics data repository" related to several experiments of failures on bearings done under different operating conditions. Furthermore, the method is compared to traditional time-feature prognostics and simulation results are given at the end of the paper. The results of the developed prognostics method, particularly the estimation of the RUL, can help improving the availability, reliability, and security while reducing the maintenance costs. Indeed, the RUL and associated confidence value are relevant information which can be used to take appropriate maintenance and exploitation decisions. In practice, this information may help the maintainers to prepare the necessary material and human resources before the occurrence of a failure. Thus, the traditional maintenance policies involving corrective and preventive maintenance can be replaced by condition based maintenance

Estimation of the remaining useful life by using Wavelet Packet Decomposition and HMMs.

International audienceThis paper deals with an estimation of the Remaining Useful Life of bearings based on the utilization of the Wavelet Packet Decomposition (WPD) and the Mixture of Gaussians Hidden Markov Models (MoG-HMM). The raw data provided by the sensors are first processed to extract features by using the wavelet packet decomposition. This latter provides a more flexible way of time-frequency representation and filtering of a signal, by allowing the use of variable sized windows and different detail levels. The extracted features are then fed as inputs of dedicated learning algorithms in order to estimate the parameters of a mixture of Gaussian Hidden Markov Model. Once this learning phase is achieved, the generated model is exploited during a second phase to continuously assess the current health state of the physical component and to estimate its remaining useful life with the associated confidence value. The proposed method is tested on a benchmark data taken from the “NASA prognostic data repository” related to several bearings'. Bearings are chosen because they are the most used and also the most faulty mechanical element in some industrial systems and process. Furthermore, the method is compared to a traditional timefeature prognostic and some simulation results are given at the end of the paper

The application of Bayesian change point detection in UAV fuel systems

AbstractA significant amount of research has been undertaken in statistics to develop and implement various change point detection techniques for different industrial applications. One of the successful change point detection techniques is Bayesian approach because of its strength to cope with uncertainties in the recorded data. The Bayesian Change Point (BCP) detection technique has the ability to overcome the uncertainty in estimating the number and location of change point due to its probabilistic theory. In this paper we implement the BCP detection technique to a laboratory based fuel rig system to detect the change in the pre-valve pressure signal due to a failure in the valve. The laboratory test-bed represents a Unmanned Aerial Vehicle (UAV) fuel system and its associated electrical power supply, control system and sensing capabilities. It is specifically designed in order to replicate a number of component degradation faults with high accuracy and repeatability so that it can produce benchmark datasets to demonstrate and assess the efficiency of the BCP algorithm. Simulation shows satisfactory results of implementing the proposed BCP approach. However, the computational complexity, and the high sensitivity due to the prior distribution on the number and location of the change points are the main disadvantages of the BCP approac

Prognostics health management: perspectives in engineering systems reliability prognostics

The Prognostic Health Management (PHM) has been asserting itself as the most promising methodology to enhance the effective reliability and availability of a product or system during its life-cycle conditions by detecting current and approaching failures, thus, providing mitigation of the system risks with reduced logistics and support costs. However, PHM is at an early stage of development, it also expresses some concerns about possible shortcomings of its methods, tools, metrics and standardization. These factors have been severely restricting the applicability of PHM and its adoption by the industry. This paper presents a comprehensive literature review about the PHM main general weaknesses. Exploring the research opportunities present in some recent publications, are discussed and outlined the general guide-lines for finding the answer to these issues.(undefined

El teatro comunitario como transformador social

Tesis de la Sede Bello Uniminuto- Seccional BelloEl presente trabajo investigativo es desarrollado en el contexto de la Comuna Dos del Barrio Santa Cruz, en donde la Corporación Cultural Nuestra Gente brinda el espacio y los recursos necesarios en cuanto a la recolección de información y apoyo de personas que hacen parte de sus procesos culturales, específicamente los jóvenes que pertenecen a los grupos de teatro que componen el quehacer principal de “Nuestra Gente”, el cual se denomina teatro comunitario. La idea nace de tres jóvenes universitarios motivados por conocer de cerca los procesos artísticos llevados a cabo por una comunidad que ha sido bastante golpeada y marcada por los procesos conflictivos de los últimos treinta años en la ciudad de Medellín, pero que al mismo tiempo se ha caracterizado por su reconocimiento y empuje transformador a través de la cultura haciendo de estas adversidades la materia prima para sus creaciones, y es precisamente este suceso paradójico el que motiva a conocer y profundizar sobre su desarrollo. La excusa perfecta para adelantar esta investigación se llama proyecto de grado como componente de un proceso de formación como Trabajadores Sociales de la Corporación Universitaria Minuto de Dios. Ubicados en este contexto, se pretende desarrollar el objetivo de la investigación analizado a la luz delos lineamientos planteados por la profesión de Trabajo Social, la cual dará cuenta de la transformación en el proyecto de vida de los jóvenes que hacen parte de los procesos artísticos de “ Nuestra Gente”, apuntando así a la construcción del tejido social, para esto se cuenta con el aporte teórico de expertos en el tema del teatro comunitario, entre estos uno muy significativo Jorge Iván Blandón, teniendo en cuenta que es el responsable de 25 años de creación artística de la mano de la comunidad que le da sentido al quehacer de la Corporación Cultural Nuestra GenteCorporación Universitaria Minuto de Dio

El teatro comunitario como transformador social

Tesis de la Sede Bello Uniminuto- Seccional BelloEl presente trabajo investigativo es desarrollado en el contexto de la Comuna Dos del Barrio Santa Cruz, en donde la Corporación Cultural Nuestra Gente brinda el espacio y los recursos necesarios en cuanto a la recolección de información y apoyo de personas que hacen parte de sus procesos culturales, específicamente los jóvenes que pertenecen a los grupos de teatro que componen el quehacer principal de “Nuestra Gente”, el cual se denomina teatro comunitario. La idea nace de tres jóvenes universitarios motivados por conocer de cerca los procesos artísticos llevados a cabo por una comunidad que ha sido bastante golpeada y marcada por los procesos conflictivos de los últimos treinta años en la ciudad de Medellín, pero que al mismo tiempo se ha caracterizado por su reconocimiento y empuje transformador a través de la cultura haciendo de estas adversidades la materia prima para sus creaciones, y es precisamente este suceso paradójico el que motiva a conocer y profundizar sobre su desarrollo. La excusa perfecta para adelantar esta investigación se llama proyecto de grado como componente de un proceso de formación como Trabajadores Sociales de la Corporación Universitaria Minuto de Dios. Ubicados en este contexto, se pretende desarrollar el objetivo de la investigación analizado a la luz delos lineamientos planteados por la profesión de Trabajo Social, la cual dará cuenta de la transformación en el proyecto de vida de los jóvenes que hacen parte de los procesos artísticos de “ Nuestra Gente”, apuntando así a la construcción del tejido social, para esto se cuenta con el aporte teórico de expertos en el tema del teatro comunitario, entre estos uno muy significativo Jorge Iván Blandón, teniendo en cuenta que es el responsable de 25 años de creación artística de la mano de la comunidad que le da sentido al quehacer de la Corporación Cultural Nuestra GenteCorporación Universitaria Minuto de Dio